Overview

Brought to you by YData

Dataset statistics

Number of variables10
Number of observations280
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory24.1 KiB
Average record size in memory88.0 B

Variable types

Numeric10

Alerts

USD-AUD is highly overall correlated with USD-CAD and 5 other fieldsHigh correlation
USD-CAD is highly overall correlated with USD-AUD and 4 other fieldsHigh correlation
USD-CHF is highly overall correlated with USD-CNY and 1 other fieldsHigh correlation
USD-CNY is highly overall correlated with USD-AUD and 3 other fieldsHigh correlation
USD-EUR is highly overall correlated with USD-AUD and 4 other fieldsHigh correlation
USD-GBP is highly overall correlated with USD-AUD and 3 other fieldsHigh correlation
USD-JPY is highly overall correlated with USD-AUD and 3 other fieldsHigh correlation
USD-NZD is highly overall correlated with USD-AUD and 4 other fieldsHigh correlation
USD-XAU is highly overall correlated with USD-CHF and 2 other fieldsHigh correlation

Reproduction

Analysis started2025-04-24 01:43:37.548046
Analysis finished2025-04-24 01:43:48.518222
Duration10.97 seconds
Software versionydata-profiling vv4.16.1
Download configurationconfig.json

Variables

USD-AUD
Real number (ℝ)

High correlation 

Distinct266
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.3181334
Minimum0.90966979
Maximum1.9696671
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2025-04-23T21:43:48.635088image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.90966979
5-th percentile0.96350263
Q11.1431185
median1.3234518
Q31.4426407
95-th percentile1.6439291
Maximum1.9696671
Range1.0599973
Interquartile range (IQR)0.29952219

Descriptive statistics

Standard deviation0.21153013
Coefficient of variation (CV)0.16047703
Kurtosis0.12216614
Mean1.3181334
Median Absolute Deviation (MAD)0.13829321
Skewness0.21541729
Sum369.07736
Variance0.044744997
MonotonicityNot monotonic
2025-04-23T21:43:48.747740image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.376841526 2
 
0.7%
1.423082396 2
 
0.7%
1.292323598 2
 
0.7%
1.316482359 2
 
0.7%
1.288327751 2
 
0.7%
1.448645516 2
 
0.7%
1.383700014 2
 
0.7%
1.535626536 2
 
0.7%
1.446549978 2
 
0.7%
1.305994515 2
 
0.7%
Other values (256) 260
92.9%
ValueCountFrequency (%)
0.9096697899 1
0.4%
0.9114939386 1
0.4%
0.9317927693 1
0.4%
0.9326618168 1
0.4%
0.9339684319 1
0.4%
0.9370314843 1
0.4%
0.9415309293 1
0.4%
0.9496676163 1
0.4%
0.9521089213 1
0.4%
0.9588647042 1
0.4%
ValueCountFrequency (%)
1.969667126 1
0.4%
1.930129319 1
0.4%
1.876876877 1
0.4%
1.857700167 1
0.4%
1.842978253 2
0.7%
1.816530427 1
0.4%
1.802776275 1
0.4%
1.782531194 1
0.4%
1.780626781 1
0.4%
1.774937877 1
0.4%

USD-CAD
Real number (ℝ)

High correlation 

Distinct267
Distinct (%)95.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.2284121
Minimum0.9431
Maximum1.6016
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2025-04-23T21:43:48.884441image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.9431
5-th percentile0.99229
Q11.08285
median1.26145
Q31.33445
95-th percentile1.468165
Maximum1.6016
Range0.6585
Interquartile range (IQR)0.2516

Descriptive statistics

Standard deviation0.15498949
Coefficient of variation (CV)0.1261706
Kurtosis-0.67242662
Mean1.2284121
Median Absolute Deviation (MAD)0.09925
Skewness0.019836783
Sum343.9554
Variance0.024021742
MonotonicityNot monotonic
2025-04-23T21:43:49.077790image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.2398 3
 
1.1%
1.0174 2
 
0.7%
1.3516 2
 
0.7%
1.3412 2
 
0.7%
1.117 2
 
0.7%
1.1657 2
 
0.7%
1.303 2
 
0.7%
1.3127 2
 
0.7%
1.354 2
 
0.7%
1.3624 2
 
0.7%
Other values (257) 259
92.5%
ValueCountFrequency (%)
0.9431 1
0.4%
0.9451 1
0.4%
0.9552 1
0.4%
0.9634 1
0.4%
0.9685 1
0.4%
0.9706 1
0.4%
0.9716 1
0.4%
0.9777 1
0.4%
0.9837 1
0.4%
0.9863 1
0.4%
ValueCountFrequency (%)
1.6016 1
0.4%
1.5949 1
0.4%
1.5891 1
0.4%
1.5868 1
0.4%
1.5842 1
0.4%
1.5718 1
0.4%
1.5677 1
0.4%
1.5653 1
0.4%
1.5585 1
0.4%
1.5584 1
0.4%

USD-CHF
Real number (ℝ)

High correlation 

Distinct273
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.0479061
Minimum0.7855
Maximum1.7193
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2025-04-23T21:43:49.207055image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.7855
5-th percentile0.87795
Q10.920725
median0.98305
Q31.15905
95-th percentile1.36425
Maximum1.7193
Range0.9338
Interquartile range (IQR)0.238325

Descriptive statistics

Standard deviation0.17433237
Coefficient of variation (CV)0.16636259
Kurtosis1.6374081
Mean1.0479061
Median Absolute Deviation (MAD)0.07285
Skewness1.3680383
Sum293.4137
Variance0.030391776
MonotonicityNot monotonic
2025-04-23T21:43:49.348657image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.9551 3
 
1.1%
0.9202 2
 
0.7%
1.0412 2
 
0.7%
0.9129 2
 
0.7%
0.9653 2
 
0.7%
0.9153 2
 
0.7%
1.7193 1
 
0.4%
0.9579 1
 
0.4%
0.9683 1
 
0.4%
0.9587 1
 
0.4%
Other values (263) 263
93.9%
ValueCountFrequency (%)
0.7855 1
0.4%
0.806 1
0.4%
0.8169 1
0.4%
0.8404 1
0.4%
0.8414 1
0.4%
0.8456 1
0.4%
0.8496 1
0.4%
0.854 1
0.4%
0.8614 1
0.4%
0.8641 1
0.4%
ValueCountFrequency (%)
1.7193 1
0.4%
1.6966 1
0.4%
1.6813 1
0.4%
1.6175 1
0.4%
1.5678 1
0.4%
1.4988 1
0.4%
1.4852 1
0.4%
1.4832 1
0.4%
1.481 1
0.4%
1.4767 1
0.4%

USD-CNY
Real number (ℝ)

High correlation 

Distinct247
Distinct (%)88.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.0347107
Minimum6.054
Maximum8.2775
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2025-04-23T21:43:49.682471image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum6.054
5-th percentile6.160135
Q16.461225
median6.83925
Q37.4096
95-th percentile8.277
Maximum8.2775
Range2.2235
Interquartile range (IQR)0.948375

Descriptive statistics

Standard deviation0.70373157
Coefficient of variation (CV)0.10003703
Kurtosis-0.84397298
Mean7.0347107
Median Absolute Deviation (MAD)0.4364
Skewness0.648475
Sum1969.719
Variance0.49523812
MonotonicityNot monotonic
2025-04-23T21:43:49.865467image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8.2765 7
 
2.5%
8.277 6
 
2.1%
8.2766 5
 
1.8%
8.2768 4
 
1.4%
8.2764 4
 
1.4%
8.2771 3
 
1.1%
8.2772 3
 
1.1%
8.2767 2
 
0.7%
6.6718 2
 
0.7%
6.3561 2
 
0.7%
Other values (237) 242
86.4%
ValueCountFrequency (%)
6.054 1
0.4%
6.0598 1
0.4%
6.093 1
0.4%
6.0942 1
0.4%
6.1129 1
0.4%
6.1191 1
0.4%
6.12 1
0.4%
6.1302 1
0.4%
6.1339 1
0.4%
6.1394 1
0.4%
ValueCountFrequency (%)
8.2775 2
 
0.7%
8.2774 2
 
0.7%
8.2773 2
 
0.7%
8.2772 3
1.1%
8.2771 3
1.1%
8.277 6
2.1%
8.2769 2
 
0.7%
8.2768 4
1.4%
8.2767 2
 
0.7%
8.2766 5
1.8%

USD-EUR
Real number (ℝ)

High correlation 

Distinct274
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.83556701
Minimum0.63339245
Maximum1.1636025
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2025-04-23T21:43:50.050043image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.63339245
5-th percentile0.68935445
Q10.75738979
median0.8343069
Q30.9060434
95-th percentile0.97928135
Maximum1.1636025
Range0.53021006
Interquartile range (IQR)0.14865361

Descriptive statistics

Standard deviation0.096092339
Coefficient of variation (CV)0.11500255
Kurtosis0.26457167
Mean0.83556701
Median Absolute Deviation (MAD)0.073257652
Skewness0.33861611
Sum233.95876
Variance0.0092337376
MonotonicityNot monotonic
2025-04-23T21:43:50.246936image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.8900756564 2
 
0.7%
0.9455370651 2
 
0.7%
0.8127438231 2
 
0.7%
0.7063144512 2
 
0.7%
0.780457348 2
 
0.7%
0.9104151493 2
 
0.7%
1.163602513 1
 
0.4%
0.8586639189 1
 
0.4%
0.8055421299 1
 
0.4%
0.8329862557 1
 
0.4%
Other values (264) 264
94.3%
ValueCountFrequency (%)
0.63339245 1
0.4%
0.6347191368 1
0.4%
0.6401229036 1
0.4%
0.6409023906 1
0.4%
0.642921435 1
0.4%
0.6588049279 1
0.4%
0.6664445185 1
0.4%
0.6729022273 1
0.4%
0.6753562504 1
0.4%
0.6793939806 1
0.4%
ValueCountFrequency (%)
1.163602513 1
0.4%
1.150218542 1
0.4%
1.147183664 1
0.4%
1.11049417 1
0.4%
1.070434596 1
0.4%
1.022913257 1
0.4%
1.020199959 1
0.4%
1.018018935 1
0.4%
1.013581999 1
0.4%
1.011940903 1
0.4%

USD-GBP
Real number (ℝ)

High correlation 

Distinct278
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.66888115
Minimum0.48081546
Maximum0.89525515
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2025-04-23T21:43:50.386656image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.48081546
5-th percentile0.50444671
Q10.60360117
median0.65161438
Q30.76131032
95-th percentile0.81179069
Maximum0.89525515
Range0.41443968
Interquartile range (IQR)0.15770915

Descriptive statistics

Standard deviation0.098734258
Coefficient of variation (CV)0.14761106
Kurtosis-1.0662352
Mean0.66888115
Median Absolute Deviation (MAD)0.089405962
Skewness-0.01533919
Sum187.28672
Variance0.0097484538
MonotonicityNot monotonic
2025-04-23T21:43:50.583424image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.7611508601 2
 
0.7%
0.6579813133 2
 
0.7%
0.7757951901 1
 
0.4%
0.7393715342 1
 
0.4%
0.7528419785 1
 
0.4%
0.7463800567 1
 
0.4%
0.7733952049 1
 
0.4%
0.7567158532 1
 
0.4%
0.7677543186 1
 
0.4%
0.7088176921 1
 
0.4%
Other values (268) 268
95.7%
ValueCountFrequency (%)
0.480815463 1
0.4%
0.4863103633 1
0.4%
0.4884482001 1
0.4%
0.4922955743 1
0.4%
0.4957612414 1
0.4%
0.4978344203 1
0.4%
0.5001250313 1
0.4%
0.5019324399 1
0.4%
0.5027399326 1
0.4%
0.5032206119 1
0.4%
ValueCountFrequency (%)
0.8952551477 1
0.4%
0.8719155986 1
0.4%
0.860437102 1
0.4%
0.8318083514 1
0.4%
0.8293249295 1
0.4%
0.8276090375 1
0.4%
0.8228420966 1
0.4%
0.822639026 1
0.4%
0.8224360556 1
0.4%
0.8216251746 1
0.4%

USD-HKD
Real number (ℝ)

Distinct212
Distinct (%)75.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.784605
Minimum7.7418
Maximum7.85
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2025-04-23T21:43:50.700975image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum7.7418
5-th percentile7.7502
Q17.7563
median7.77795
Q37.800025
95-th percentile7.846815
Maximum7.85
Range0.1082
Interquartile range (IQR)0.043725

Descriptive statistics

Standard deviation0.03074889
Coefficient of variation (CV)0.0039499615
Kurtosis-0.70088752
Mean7.784605
Median Absolute Deviation (MAD)0.02205
Skewness0.65438444
Sum2179.6894
Variance0.00094549424
MonotonicityNot monotonic
2025-04-23T21:43:50.854651image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.7503 6
 
2.1%
7.7501 5
 
1.8%
7.75 5
 
1.8%
7.7994 5
 
1.8%
7.7551 4
 
1.4%
7.7502 4
 
1.4%
7.7998 3
 
1.1%
7.8 3
 
1.1%
7.7531 3
 
1.1%
7.7993 2
 
0.7%
Other values (202) 240
85.7%
ValueCountFrequency (%)
7.7418 1
 
0.4%
7.75 5
1.8%
7.7501 5
1.8%
7.7502 4
1.4%
7.7503 6
2.1%
7.7504 2
 
0.7%
7.7505 2
 
0.7%
7.7506 1
 
0.4%
7.7507 2
 
0.7%
7.7508 1
 
0.4%
ValueCountFrequency (%)
7.85 2
0.7%
7.8499 1
0.4%
7.8498 2
0.7%
7.8497 1
0.4%
7.8496 1
0.4%
7.8494 1
0.4%
7.8493 1
0.4%
7.8491 2
0.7%
7.8488 1
0.4%
7.8483 1
0.4%

USD-JPY
Real number (ℝ)

High correlation 

Distinct275
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean111.14521
Minimum76.27
Maximum160.88
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2025-04-23T21:43:50.990470image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum76.27
5-th percentile80.371
Q1102.5825
median110.39
Q3119.12
95-th percentile148.743
Maximum160.88
Range84.61
Interquartile range (IQR)16.5375

Descriptive statistics

Standard deviation17.956715
Coefficient of variation (CV)0.16156085
Kurtosis0.36445028
Mean111.14521
Median Absolute Deviation (MAD)8.34
Skewness0.40207818
Sum31120.66
Variance322.44363
MonotonicityNot monotonic
2025-04-23T21:43:51.169777image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
111.39 2
 
0.7%
115.77 2
 
0.7%
106.28 2
 
0.7%
112.69 2
 
0.7%
149.98 2
 
0.7%
111.49 1
 
0.4%
109.98 1
 
0.4%
110.26 1
 
0.4%
112.39 1
 
0.4%
110.78 1
 
0.4%
Other values (265) 265
94.6%
ValueCountFrequency (%)
76.27 1
0.4%
76.66 1
0.4%
76.76 1
0.4%
76.91 1
0.4%
77.06 1
0.4%
77.62 1
0.4%
77.96 1
0.4%
78.12 1
0.4%
78.17 1
0.4%
78.32 1
0.4%
ValueCountFrequency (%)
160.88 1
0.4%
157.8 1
0.4%
157.31 1
0.4%
157.2 1
0.4%
155.19 1
0.4%
152.03 1
0.4%
151.68 1
0.4%
151.35 1
0.4%
150.63 1
0.4%
149.98 2
0.7%

USD-NZD
Real number (ℝ)

High correlation 

Distinct270
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4863156
Minimum1.1372683
Maximum2.402691
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2025-04-23T21:43:51.300054image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1.1372683
5-th percentile1.204812
Q11.3608242
median1.4558163
Q31.5821533
95-th percentile1.8381284
Maximum2.402691
Range1.2654227
Interquartile range (IQR)0.22132912

Descriptive statistics

Standard deviation0.21577264
Coefficient of variation (CV)0.14517283
Kurtosis2.9600658
Mean1.4863156
Median Absolute Deviation (MAD)0.11911091
Skewness1.3497739
Sum416.16837
Variance0.046557832
MonotonicityNot monotonic
2025-04-23T21:43:51.460555image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.433897333 2
 
0.7%
1.361841209 2
 
0.7%
1.483679525 2
 
0.7%
1.425110446 2
 
0.7%
1.460493647 2
 
0.7%
1.294163323 2
 
0.7%
1.475361464 2
 
0.7%
1.455180442 2
 
0.7%
1.375515818 2
 
0.7%
1.511258879 2
 
0.7%
Other values (260) 260
92.9%
ValueCountFrequency (%)
1.137268282 1
0.4%
1.141813199 1
0.4%
1.154334526 1
0.4%
1.160496693 1
0.4%
1.167815018 1
0.4%
1.170823089 1
0.4%
1.176470588 1
0.4%
1.176609013 1
0.4%
1.192037192 1
0.4%
1.192179304 1
0.4%
ValueCountFrequency (%)
2.402691014 1
0.4%
2.371354043 1
0.4%
2.270663034 1
0.4%
2.235636038 1
0.4%
2.150075253 1
0.4%
2.132650885 1
0.4%
2.131741633 1
0.4%
2.080732418 1
0.4%
2.058036633 1
0.4%
2.052966537 1
0.4%

USD-XAU
Real number (ℝ)

High correlation 

Distinct239
Distinct (%)85.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0011176571
Minimum0.000301
Maximum0.00353
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2025-04-23T21:43:51.586685image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.000301
5-th percentile0.00048315
Q10.0006005
median0.000792
Q30.00129325
95-th percentile0.0028705
Maximum0.00353
Range0.003229
Interquartile range (IQR)0.00069275

Descriptive statistics

Standard deviation0.00076946758
Coefficient of variation (CV)0.68846478
Kurtosis1.0365617
Mean0.0011176571
Median Absolute Deviation (MAD)0.0002295
Skewness1.4810572
Sum0.312944
Variance5.9208036 × 10-7
MonotonicityNot monotonic
2025-04-23T21:43:51.738481image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.00229 3
 
1.1%
0.000755 3
 
1.1%
0.000788 3
 
1.1%
0.000757 3
 
1.1%
0.000565 3
 
1.1%
0.000547 2
 
0.7%
0.00076 2
 
0.7%
0.00239 2
 
0.7%
0.00233 2
 
0.7%
0.000849 2
 
0.7%
Other values (229) 255
91.1%
ValueCountFrequency (%)
0.000301 1
0.4%
0.00032 1
0.4%
0.00035 1
0.4%
0.000357 1
0.4%
0.000364 1
0.4%
0.000378 1
0.4%
0.00038 1
0.4%
0.000381 1
0.4%
0.000399 1
0.4%
0.000409 1
0.4%
ValueCountFrequency (%)
0.00353 1
0.4%
0.00337 1
0.4%
0.0033 1
0.4%
0.00329 1
0.4%
0.00324 1
0.4%
0.00319 1
0.4%
0.00318 1
0.4%
0.00314 2
0.7%
0.00309 1
0.4%
0.00306 1
0.4%

Interactions

2025-04-23T21:43:47.172982image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:37.760597image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:38.818134image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:39.987767image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:40.902823image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:41.953040image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:42.987640image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:44.095335image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:45.017362image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:46.038552image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:47.291507image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:37.894009image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:38.919407image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:40.083931image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:41.013505image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:42.035239image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:43.119959image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:44.167851image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:45.107906image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:46.154424image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:47.426133image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:38.014080image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:39.037251image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:40.182877image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:41.130315image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:42.119024image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:43.217286image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:44.278759image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:45.210937image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:46.253203image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:47.536968image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:38.124418image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:39.155118image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:40.255441image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:41.231790image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:42.231512image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:43.318184image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:44.368992image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:45.456329image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:46.359194image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:47.626540image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:38.239956image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:39.293115image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:40.327535image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:41.306618image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:42.346745image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:43.404294image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:44.473098image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:45.543537image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:46.448300image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:47.735207image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:38.327796image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:39.373857image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:40.414127image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:41.420844image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:42.432550image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:43.543996image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:44.553299image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:45.627700image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:46.573197image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:47.846726image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:38.423955image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:39.477396image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:40.541693image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:41.511358image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:42.527085image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:43.660697image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:44.640925image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:45.698867image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:46.711246image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:47.952323image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:38.530521image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:39.581119image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:40.613451image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:41.652053image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:42.619745image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:43.761816image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:44.720844image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:45.775678image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:46.818197image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:48.033670image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:38.616225image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:39.677717image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:40.702570image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:41.728820image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:42.710995image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:43.852921image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:44.816693image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:45.860340image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:46.910431image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:48.143517image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:38.707086image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:39.768048image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:40.797805image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:41.833307image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:42.829898image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:43.971823image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:44.916329image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:45.947956image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-23T21:43:47.048324image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2025-04-23T21:43:51.847004image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
USD-AUDUSD-CADUSD-CHFUSD-CNYUSD-EURUSD-GBPUSD-HKDUSD-JPYUSD-NZDUSD-XAU
USD-AUD1.0000.9140.1900.5560.8260.5330.3780.7050.9270.004
USD-CAD0.9141.0000.1190.4730.8750.5860.3700.6800.805-0.024
USD-CHF0.1900.1191.0000.655-0.018-0.4630.0830.0930.3210.901
USD-CNY0.5560.4730.6551.0000.266-0.1770.3570.4410.6400.506
USD-EUR0.8260.875-0.0180.2661.0000.7270.3650.7230.689-0.205
USD-GBP0.5330.586-0.463-0.1770.7271.0000.2860.3300.394-0.664
USD-HKD0.3780.3700.0830.3570.3650.2861.0000.4580.330-0.071
USD-JPY0.7050.6800.0930.4410.7230.3300.4581.0000.626-0.005
USD-NZD0.9270.8050.3210.6400.6890.3940.3300.6261.0000.114
USD-XAU0.004-0.0240.9010.506-0.205-0.664-0.071-0.0050.1141.000

Missing values

2025-04-23T21:43:48.317260image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-04-23T21:43:48.427145image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

USD-AUDUSD-CADUSD-CHFUSD-CNYUSD-EURUSD-GBPUSD-HKDUSD-JPYUSD-NZDUSD-XAU
DATE
2002-02-011.9696671.58911.71938.27661.1636030.7088187.7993134.682.4026910.00353
2002-03-011.9301291.60161.69668.27651.1502190.7055177.7994133.362.3713540.00337
2002-04-011.8768771.59491.68138.27741.1471840.7013117.7998132.732.2706630.00330
2002-05-011.8577001.56771.61758.27731.1104940.6858717.7991128.542.2356360.00324
2002-06-011.7624251.52791.56788.27651.0704350.6871447.7998124.222.0807320.00306
2002-07-011.7749381.51741.48108.27711.0085730.6521037.7994119.472.0529670.00318
2002-08-011.8429781.58421.48528.27661.0229130.6395097.7999119.852.1500750.00329
2002-09-011.8165301.55851.49888.27681.0180190.6449537.8000118.462.1317420.00319
2002-10-011.8429781.58681.47528.27721.0135820.6375927.7997121.812.1326510.00309
2002-11-011.8027761.55841.47678.27721.0097950.6389377.7996122.482.0580370.00314
USD-AUDUSD-CADUSD-CHFUSD-CNYUSD-EURUSD-GBPUSD-HKDUSD-JPYUSD-NZDUSD-XAU
DATE
2024-08-011.5285851.38080.87807.22670.9237020.7778477.8125149.981.6803900.000409
2024-09-011.4781971.34920.84967.09130.9051410.7617897.7977146.171.6002560.000399
2024-10-011.4465501.35250.84567.01870.8980690.7476647.7730143.631.5750510.000380
2024-11-011.5192951.39340.86417.11800.9187800.7752547.7734152.031.6730800.000364
2024-12-011.5356271.40060.88107.24670.9454480.7852387.7820149.771.6903310.000378
2025-01-011.6160311.43840.90747.29930.9658100.7989777.7686157.201.7876300.000381
2025-02-011.6082341.45410.91097.24460.9650650.8067777.7924155.191.7749380.000357
2025-03-011.6105651.44610.90317.27840.9638550.7951027.7787150.631.7863520.000350
2025-04-011.6007681.43870.88437.25690.9245560.7741147.7805149.961.7611840.000320
2025-05-011.5681351.38490.81697.29970.8775780.7527857.7625142.181.6840690.000301